2) Parallel PixelHop. A PixelHop unit consists of a set of filters
of the same size that operate on all pixels in a block in parallel. A
filter is a 3D tensor of size \((s,s,c)\) , where \(s\) x\(s\)  are the spatial
dimensions and \(c\)  is the spectral dimension. Typically, \(s=2,3,4\)  and
\(c=3\)  for color images. We employ multiple PixelHop units in parallel for feature
extraction to increase feature diversity. Filter weights are determined
by a variant of PCA called the Saab transform
[1]}. As shown in Fig. REF , we use
three parallel PixelHop units for feature extraction, where the filters are
of sizes 2x2x3, 3x3x3 and 4x4x3, respectively. For filters of sizes
\((s,s,c)\) , there are \(s^2 c\)  channels and each channel has \((17-s)^2\) 
spatial responses.
